relation: https://digilib.uin-suka.ac.id/id/eprint/67440/
title: MODEL ENSEMBEL CONVOLUTIONAL NEURAL NETWORK (CNN) MENGGUNAKAN RANDOM SEARCH UNTUK DETEKSIPNEUMONIA BERDASARKAN CHEST X-RAY
creator: Irma Eryanti Putri, NIM.: 22206052007
subject: 004 Pemrosesan Data, Ilmu Komputer, Teknik Informatika
description: Pneumonia is an infection caused by bacteria, viruses and fungi  in the air sacs in the lungs, which can cause disorders such as coughing up  phlegm, fever, chills, nausea, vomiting, fatigue and shortness of breath. If  pneumonia is not treated quickly and appropriately it can result in death,  therefore early detection of pneumonia is a solution to prevent pneumonia.  This research detects pneumonia from Chest X-ray data with an ensemble  of Convolutional Neural Network (CNN) models such as ResNet50,  MobileNetV2, DenseNet169, To detect pneumonia, this research has  several stages, namely collecting Chest The results of pneumonia detection  with the Ensemble CNN model using Random Search on the Chest X-ray  dataset obtained training accuracy of 0.92%, testing accuracy of 0.92% and  validation accuracy of 0.93%. Evaluation of the Confusion Matrix  Ensemble CNN model using Random Search obtained an accuracy of  0.94%, recall of 1.00%, precision of 0.89% and f1-score of 0.94%.
date: 2024-08-23
type: Thesis
type: NonPeerReviewed
format: text
language: id
identifier: https://digilib.uin-suka.ac.id/id/eprint/67440/1/22206052007_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf
format: text
language: id
identifier: https://digilib.uin-suka.ac.id/id/eprint/67440/2/22206052007_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf
identifier:   Irma Eryanti Putri, NIM.: 22206052007  (2024) MODEL ENSEMBEL CONVOLUTIONAL NEURAL NETWORK (CNN) MENGGUNAKAN RANDOM SEARCH UNTUK DETEKSIPNEUMONIA BERDASARKAN CHEST X-RAY.  Masters thesis, UIN SUNAN KALIJAGA YOGYAKARTA.